Memory based on abstraction for dynamic fitness functions.

Simple item page
dc.contributor.authorRichter, Hendriken
dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2013-06-13T12:47:58Z
dc.date.available2013-06-13T12:47:58Z
dc.date.issued2008
dc.description.abstractThis paper proposes a memory scheme based on abstraction for evolutionary algorithms to address dynamic optimization problems. In this memory scheme, the memory does not store good solutions as themselves but as their abstraction, i.e., their approximate location in the search space. When the environment changes, the stored abstraction information is extracted to generate new individuals into the population. Experiments are carried out to validate the abstraction based memory scheme. The results show the efficiency of the abstraction based memory scheme for evolutionary algorithms in dynamic environments.en
dc.identifier.citationRichter, H. and Yang, S. (2008) Memory based on abstraction for dynamic fitness functions.In: Applications of Evolutionary Computing EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008. Berlin: Springer-Verlag, pp. 596-605.en
dc.identifier.doihttps://doi.org/10.1007/978-3-540-78761-7_65
dc.identifier.isbn978-3-540-78760-0
dc.identifier.urihttp://hdl.handle.net/2086/8731
dc.language.isoenen
dc.peerreviewedYesen
dc.publisherSpringer- Verlag.en
dc.relation.ispartofseriesLecture notes in computer science;Vol. 4974
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.titleMemory based on abstraction for dynamic fitness functions.en
dc.typeArticleen

Files

License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
3.18 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

School of Computer Science and Informatics